Use of satellite images to assess water quality in reservoirs used in public supply: with emphasis on chlorophyll a

• Grant number: 25/17963-3
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: November 01, 2025
• End date: January 31, 2026
• Field of knowledge: Engineering - Sanitary Engineering - Water Resources
• Principal Investigator: Marcelo Luiz Martins Pompêo
• Grantee: Camilla Yamanaka
• Supervisor: Jesus Valeriano Delegido Gomez
• Host Institution: Instituto de Biociências (IB). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Universitat de València, Spain
• Associated to the scholarship: 24/08719-9 - Use of satellite images to assess water quality in reservoirs used in public supply: with emphasis on chlorophyll a, BP.IC

Abstract

Monitoring water quality in public supply reservoirs is essential for environmental management, especially in tropical regions subject to cyanobacterial blooms. Chlorophyll-a, a photosynthetic pigment present in all phytoplankton groups, is widely used as an indicator of algal biomass and eutrophication. The use of orbital remote sensing, particularly with images from the European Space Agency's (ESA) Sentinel-2 satellites, has become a promising tool for estimating chlorophyll-a and other bio-optical parameters. However, the performance of the native algorithms available in the SNAP (Sentinel Application Platform) software may vary depending on water optical properties, such as turbidity, dissolved organic matter, and phytoplankton composition, making their validation under different environmental conditions necessary. Within the scope of the undergraduate research fellowship, an empirical linear regression model relating in situ chlorophyll-a and cyanobacterial density has already been developed. This model proved to be statistically robust, with a high coefficient of determination (R²) and low error values (RMSE, NRMSE). It enabled the initial validation of chlorophyll-a as a predictor of cyanobacterial biomass. In addition, Sentinel-2 images were processed for the main reservoirs that supply the São Paulo Metropolitan Region, with atmospheric corrections applied in SNAP, providing a solid foundation for subsequent stages of the project. The internship at the Image Processing Laboratory (IPL) of the University of Valencia will allow for a systematic evaluation of the accuracy of SNAP's native algorithms in estimating chlorophyll-a, comparing them with field data. If limitations are observed, alternatives will be tested, such as spectral adjustments, application of multivariate regressions, and the use of the ARTMO toolbox for the development of customized algorithms adapted to the optical conditions of Brazilian inland waters. The variable phycocyanin, an accessory pigment exclusive to cyanobacteria and recognized as a more specific marker for this group, will also be incorporated, with the potential to improve the accuracy of estimates and contribute to risk management associated with blooms. The project includes detailed statistical analysis (R², RMSE, MAE, MAPE) and the generation of thematic maps of chlorophyll-a and phycocyanin estimates, aiming at systematic comparisons among algorithms. The international experience will bring academic gains by consolidating technical skills in image processing and the development of bio-optical algorithms, as well as strengthening integration with leading research groups in remote sensing and limnology. Expected results include: validation of the performance of SNAP's native algorithms under tropical conditions; development of specific algorithms for Brazilian inland waters; incorporation of new bio-optical parameters (phycocyanin) into the analysis; and knowledge transfer to the research group in Brazil through training sessions, technical manuals, conference presentations, and scientific publications. Thus, the internship will make a significant contribution to advancing research on water quality in supply reservoirs and to the training of highly qualified human resources at the interface between limnology and remote sensing. (AU)